Journal article Open Access

COSIFER: a Python package for the consensus inference of molecular interaction networks

Manica, M.; Bunne, C.; Mathis, R.; Cadow, J.; Ahsen, M.; Stolovitzky; Martínez, M.

Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Manica, M.</dc:creator>
  <dc:creator>Bunne, C.</dc:creator>
  <dc:creator>Mathis, R.</dc:creator>
  <dc:creator>Cadow, J.</dc:creator>
  <dc:creator>Ahsen, M.</dc:creator>
  <dc:creator>Martínez, M.</dc:creator>
  <dc:description>The advent of high-throughput technologies has provided researchers with measurements of thousands of molecular entities and enable the investigation of the internal regulatory apparatus of the cell. However, network inference from high-throughput data is far from being a solved problem. While a plethora of different inference methods have been proposed, they often lead to non-overlapping predictions, and many of them lack user-friendly implementations to enable their broad utilization. Here, we present Consensus Interaction Network Inference Service (COSIFER), a package and a companion web-based platform to infer molecular networks from expression data using state-of-the-art consensus approaches. COSIFER includes a selection of state-of-the-art methodologies for network inference and different consensus strategies to integrate the predictions of individual methods and generate robust networks.
  <dc:title>COSIFER: a Python package for the consensus inference of molecular interaction networks</dc:title>
Views 72
Downloads 66
Data volume 19.4 MB
Unique views 68
Unique downloads 65


Cite as